Without constant attention to how accurately reference information is maintained in the accounting system, it is impossible to achieve high-quality reporting. An employee who operates with a system can forget to specify the values of one or more customer or product dimensions. These are precisely called "holes", that immediately appear in the reports.
For example, an employee of a company, while working with the accounting system, forgot to enter the type of product on the invoice for several goods. As a result, an array of data contains an indefinite group of data, which can be defined if the employee returns to the original invoices again. It will be easy to find the mistake if the parameters are empty. But what should one do if information is entered with an error? For instance, the attribute of the client is incorrectly specified and the sales KPI is calculated with errors.
Among the main measures to combat input errors, departments often appoint an employee who, once in a certain period (week or month), is engaged in data verification. This not only creates unnecessary labor costs, but can also multiply errors. For example, an employee can also attribute some indicator to the wrong classification. As a result, we are again faced with the need to double-check the data.
Another method is cross-validation. We can try to find related analytics and compare them with each other. For example, let's take the "sales manager" analytics and compare it with the "channel of sales" parameter and display both parameters for comparison. We know that a company has a special department for sales in the HORECA segment, so the presence of data on the retail sales department in their reporting will look strange. Upon closer view, it may turn out that a number of companies are incorrectly included in the list of the HORECA segment. Although the error has been eliminated, it requires a deeper understanding of the company's business processes and the functional responsibility of certain employees.
The high turnover of the company's staff can present a particular challenge for the development of such analytics. The knowledge base cannot be accumulated properly, as approaches to the organization of work often change. As a result, constant adjustments to the reference information for reporting may be required.
All this leads to the need for automation of the controlling process and introduction of a special corporate system that can store information in multi-dimensional structures. Spreadym independently checks data entered by the user in a universal form. If a required parameter is not entered or entered with an error, the system will send a notification that the data cannot be submitted to the database.
